Troubleshooting#
Error messages#
docker: Error response from daemon: OCI runtime create failed: container_linux.go:345: starting container process caused "process_linux.go:424: container init caused \"process_linux.go:407: running prestart hook 1 caused \\\"error running hook: exit status 1, stdout: , stderr: exec command: [/usr/bin/nvidia-container-cli --load-kmods configure --ldconfig=@/sbin/ldconfig --device=all --compute --utility --require=cuda>=10.0 brand=tesla,driver>=384,driver<385 brand=tesla,driver>=410,driver<411 --pid=35777 /var/lib/docker/devicemapper/mnt/7b5b6d59cd4fe9307b7523f1cc9ce3bc37438cc793ff4a5a18a0c0824ec03982/rootfs]\\\\nnvidia-container-cli: requirement error: unsatisfied condition: brand = tesla\\\\n\\\"\"": unknown.
If you see the above error message, the GPU hardware and/or NVIDIA drivers installed on the agent are not compatible with CUDA 10, but you are trying to run a Docker image that depends on CUDA 10. Please run the commands below; if the first succeeds and the second fails, you should be able to use Determined as long as you use Docker images based on CUDA 9.
docker run --gpus all --rm nvidia/cuda:9.0-runtime nvidia-smi
docker run --gpus all --rm nvidia/cuda:10.0-runtime nvidia-smi
Debug Database Migration Failures#
Dirty database version <a long number>. Fix and force version.
If you see the above error message, a database migration was likely interrupted while running and the database is now in a dirty state.
Make sure you back up the database and temporarily shut down the master before proceeding further.
To fix this error message, locate the up migration with a suffix of .up.sql and a prefix
matching the long number in the error message in this directory
<https://github.com/determined-ai/determined/tree/master/master/static/migrations>_ and carefully
run the SQL within the file manually against the database used by Determined. For convenience, all
the information needed to connect except the password can be found with:
det master config | jq .db
If this proceeds successfully, then mark the migration as successful by running the following SQL:
UPDATE schema_migrations SET dirty = false;
And restart the master. Otherwise, please seek assistance in the community Slack.
Validate NVIDIA Container Toolkit#
To verify that a Determined agent instance can run containers that use GPUs, run:
docker run --gpus all --rm debian:10-slim nvidia-smi
You should see output that describes the GPUs available on the agent instance, such as:
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 418.39 Driver Version: 418.39 CUDA Version: 10.1 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 GeForce GTX 108... Off | 00000000:05:00.0 Off | N/A |
| 56% 84C P2 177W / 250W | 10729MiB / 11176MiB | 76% Default |
+-------------------------------+----------------------+----------------------+
| 1 GeForce GTX 108... Off | 00000000:06:00.0 Off | N/A |
| 28% 62C P0 56W / 250W | 0MiB / 11178MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 2 GeForce GTX 108... Off | 00000000:09:00.0 Off | N/A |
| 31% 64C P0 57W / 250W | 0MiB / 11178MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 3 TITAN Xp Off | 00000000:0A:00.0 Off | N/A |
| 20% 36C P0 57W / 250W | 0MiB / 12196MiB | 6% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| 0 4638 C python3 10719MiB |
+-----------------------------------------------------------------------------+